Habitat mapping for vulnerable species is critical to assessing reserve design alternatives in terms of conservation goals. Habitat distributions for many of the vulnerable species are poorly known and published accounts of known populations are few; therefore, habitat modeling based on environmental characteristics was conducted in order to provide the most complete, scientifically based depiction of species habitat. Recognizing the critical knowledge of many Pima County biologists, these “expert reviewers” were asked to be part of the modeling process. Reviewers identified key environmental variables describing habitat and helped GIS analysts score environmental characteristics for each species. Analysts then built GIS models based on these environmental parameters resulting in maps of high, medium, and low potential habitat. Biologists were then asked to review habitat maps and revise model parameters if necessary. This iterative process of GIS analysis and biological review resulted in refined models that more closely represented vulnerable species habitat.
During this process, data gaps were identified and filled with new and updated mapping for most environmental variables. After model parameters were finalized and the GIS approach refined, remaining errors in habitat distribution were corrected manually by reviewers. For example, biogeographical ranges were delineated and applied to final models to reduce the extent of predicted habitat to more closely represent the true potential range of the species. This final step improved the accuracy of habitat maps.
Although mapping potential species habitat is critical to reserve design and assessment, mapping locations of known populations and critical areas for conservation are also important. Therefore, HDMS, the most extensive published database of species known locations, was used in mapping and conservation goals assessment. This database was continually augmented with locations mapped by species experts throughout the map review process. Expert reviewers, coordinated by SRG, were also asked to delineate and describe priority areas for conservation for each vulnerable species. Priority conservation area 1 designates areas that experts believe are critical to include in the reserve system, priority conservation area 2 designates areas that are of value to the reserve system, priority conservation area 3 designates areas important for habitat connectivity, and priority conservation area 4 designates areas with potential for habitat restoration. A thorough discussion of this effort is included in the forthcoming report, “Priority Conservation Areas”, June 2001. Priority conservation areas and all known locations are shown together with modeled habitat in each species account.
GIS was used to generate habitat models for species by summarizing key environmental characteristics that comprise species habitat. After identifying important environmental variables, each environmental characteristic was scored as potential habitat for each species. These species-habitat scores are compiled in a species-environment matrix where each characteristic (i.e., mixed grass-scrub) of a variable (i.e., vegetation) is valued from low to high (1-3) for each species. Environmental characteristics that have no value to species are scored 0, and characteristics which act as barriers to habitat are scored as “MASK”, which means the areas they cover are excluded from potential habitat in the model.
Variables used in the models are vegetation/land cover, plus urban, meso-riparian and xero-riparian, perennial and intermittent streams, shallow groundwater, springs, elevation, slope, aspect, landform, cave/mine potential, geology, and soils. A total of 115 characteristics for these 15 variables were scored as potential habitat for each species. Characteristics of these variables are well understood for some species (such as a fish requiring a perennial stream), but many are not. In some cases, a “best guess” was recorded in the table cells of the species-environment matrix. All scores have been reviewed and revised by species experts.
The species-environment matrix then served to define model parameters for GIS grid analysis. In the GIS, each variable exists as a data layer comprised of regular 100 m grid cells covering the entire county. New grids are created for each species, with grid cell values storing habitat scores from the species-environment matrix. In the GIS modeling process, grids that comprise habitat for a species are “stacked” on top of one another. Grid cell stacks are then added to create a new grid that represents the sum of all environmental characteristics for a species. This grid is the habitat model.
The quality of resulting GIS models depends on both the accuracy and resolution of environmental variable mapping and the appropriate scoring of environmental characteristics for each species. The advantage of using GIS is that it is an unbiased, systematic approach to synthesizing large amounts of information. Furthermore, all model parameters are explicit which facilitates review and revision. Multiple updates to GIS data layers for environmental variables and species scores in the species-environment matrix have been made during the last 12 months and are ongoing, so models will continue to improve.